Evaluation of Different Heat Flux Products Over the Tropical Indian Ocean. Issue 6 (5th June 2020)

• Record Type: Journal Article
• Authors: Pokhrel, Samir; Dutta, Ushnanshu; Rahaman, Hasibur; Chaudhari, Hemantkumar; Hazra, Anupam; Saha, Subodh Kumar; Veeranjaneyulu, Chinta
• Is Part Of: Earth and space science. Volume 7:Issue 6(2020)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2020-06-05
• Subjects: net heat flux -- ERA5 -- CFSR -- buoy data -- Indian Ocean; Space sciences -- Periodicals; Geophysics -- Periodicals; 500.5
• DOI: 10.1029/2019EA000988
• Languages: English
• ISSNs: 2333-5084

Abstract

Abstract: Net heat flux (Qnet) and its components from four reanalysis (NCEP‐2, CFSR, ERA5, and MERRA) and two blended products (OAFlux & TropFlux) are compared with in situ observation (two Research Moored Array for African‐Asian‐Australian Monsoon Analysis and Prediction buoys and one Woods Hole Oceanographic Institution buoy) over the north Indian Ocean to quantify their uncertainties in daily, seasonal, and annual scales. These comparisons provide the present status of Qnet error in most state of the art reanalysis/blended products. The root‐mean‐square error (RMSE) remains similar to the RMSE a decade earlier, despite more observation and improved models and reanalysis methods. However, there is a clear separation of flux quality from the older generation of reanalysis (NCEP‐2) to the newer production of reanalysis (MERRA, CFSR, and ERA5). While individually ERA5 provides the best estimate, the ensemble mean (i.e., average of ERA5, CFSR, MERRA, TropFlux, and OAFlux) is very close to ERA5 both in terms of correlations and RMSE and provides the most reliable estimate by virtue of removal of some of the uncertainties in estimation of flux by each of the flux products. A significant reduction of RMSE in Qnet estimates from 100 W/m 2 (in NCEP‐2) to 45 W/m 2 (in the ensemble mean) is considerable progress. It is noteworthy that all the recent flux products estimate the increasing trend of Qnet in the north Bay of Bengal and subseasonal fluctuations with significant fidelity. Also, in the south of equator location vigorous subseasonal fluctuations in boreal winter are well captured. We believe that this is significant progress in the estimation of Qnet over the Indian Ocean. Key Points: Surface net heat flux is compared in recent reanalysis and blended products The flux quality has improved significantly as compared to older generation reanalysis Ensemble mean net heat flux is the new data much better than individual flux data with least RMSE and almost comparable correlations